Hierarchical Bayesian Optimization Algorithm by Pelikan Martin (26 results)

Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

hardcover. Condition: Good. Ex-library book with typical stickers and stampings. Priority Mail is available on this item. No international shipping.

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Condition: New. pp. 186.

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Condition: New. pp. 188.

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PF. Condition: New.

Condition: New. In English.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional variation operators of evolutionary algorithms, by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). They provide a scalable solution to a broad class of problems. The book provides an overview of evolutionary algorithms that use probabilistic models to guide their search, motivates and describes BOA and hBOA in a way accessible to a wide audience, and presents numerous results confirming that they are revolutionary approaches to black-box optimization.…

Gebunden. Condition: New. Presents a new generation of evolutionary algorithms, which are revolutionary approaches to black-box optimizationThis book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms .

Taschenbuch. Condition: Neu. Hierarchical Bayesian Optimization Algorithm | Toward a New Generation of Evolutionary Algorithms | Martin Pelikan | Taschenbuch | Studies in Fuzziness and Soft Computing | xviii | Englisch | 2010 | Springer | EAN 9783642062735 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Condition: new. Questo è un articolo print on demand.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional variation operators of evolutionary algorithms, by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). They provide a scalable solution to a broad class of problems. The book provides an overview of evolutionary algorithms that use probabilistic models to guide their search, motivates and describes BOA and hBOA in a way accessible to a wide audience, and presents numerous results confirming that they are revolutionary approaches to black-box optimization. 184 pp. Englisch.…

Condition: New. Print on Demand pp. 188 Illus.

Condition: New. Print on Demand pp. 186 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 188.

Condition: New. PRINT ON DEMAND pp. 186.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a new generation of evolutionary algorithms, which are revolutionary approaches to black-box optimizationThis book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms .…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional variation operators of evolutionary algorithms, by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). They provide a scalable solution to a broad class of problems. The book provides an overview of evolutionary algorithms that use probabilistic models to guide their search, motivates and describes BOA and hBOA in a way accessible to a wide audience, and presents numerous results confirming that they are revolutionary approaches to black-box optimization.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 184 pp. Englisch.…